{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data loader testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/yoyee/Documents/deepSfm\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import sys\n",
    "module_path = os.path.abspath(os.path.join('..'))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)\n",
    "os.chdir('../')\n",
    "print(os.getcwd())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:100% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import logging\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "from IPython.core.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:100% !important; }</style>\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def loadConfig(filename):\n",
    "    import yaml\n",
    "    with open(filename, 'r') as f:\n",
    "        config = yaml.load(f)\n",
    "    return config\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "config path:  configs/superpoint_coco_test.yaml\n",
      "config:  {'data': {'name': 'coco', 'dataset': 'coco', 'labels': 'magicpoint_synth20_homoAdapt100_coco/predictions', 'cache_in_memory': False, 'validation_size': 10, 'preprocessing': {'resize': [240, 320]}, 'augmentation': {'photometric': {'enable': True, 'primitives': ['random_brightness', 'random_contrast', 'additive_speckle_noise', 'additive_gaussian_noise', 'additive_shade', 'motion_blur'], 'params': {'random_brightness': {'max_abs_change': 50}, 'random_contrast': {'strength_range': [0.5, 1.5]}, 'additive_gaussian_noise': {'stddev_range': [0, 10]}, 'additive_speckle_noise': {'prob_range': [0, 0.0035]}, 'additive_shade': {'transparency_range': [-0.5, 0.5], 'kernel_size_range': [100, 150]}, 'motion_blur': {'max_kernel_size': 3}}}, 'homographic': {'enable': False}}, 'warped_pair': {'enable': True, 'params': {'translation': True, 'rotation': True, 'scaling': True, 'perspective': True, 'scaling_amplitude': 0.2, 'perspective_amplitude_x': 0.2, 'perspective_amplitude_y': 0.2, 'patch_ratio': 0.85, 'max_angle': 1.57, 'allow_artifacts': True}, 'valid_border_margin': 3}}, 'model': {'name': 'magic_point', 'batch_size': 1, 'eval_batch_size': 1, 'learning_rate': 0.0001, 'detection_threshold': 0.015, 'descriptor_dist': 7.5, 'lambda_d': 800, 'lambda_loss': 1, 'nn_thresh': 0.7, 'nms': 4}, 'retrain': True, 'reset_iter': True, 'train_iter': 200, 'validation_interval': 100, 'save_interval': 40, 'pretrained': '../deepSfm/logs/superpoint_kitti30_1/checkpoints/superPointNet_170000_checkpoint.pth.tar'}\n"
     ]
    }
   ],
   "source": [
    "# load config\n",
    "logging.basicConfig(format='[%(asctime)s %(levelname)s] %(message)s',\n",
    "                        datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO)\n",
    "\n",
    "\n",
    "filename = 'configs/superpoint_coco_test.yaml'\n",
    "# filename = 'configs/magicpoint_repeatability.yaml'\n",
    "config = loadConfig(filename)\n",
    "print(\"config path: \", filename)\n",
    "print(\"config: \", config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "task:  coco\n",
      "load labels from:  magicpoint_synth20_homoAdapt100_coco/predictions/train\n",
      "load labels from:  magicpoint_synth20_homoAdapt100_coco/predictions/val\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[04/25/2019 14:52:45 INFO] == train split size 82783 in 82783 batches, val split size 40504 in 40504 batches\n"
     ]
    }
   ],
   "source": [
    "task = config['data']['dataset']\n",
    "print(\"task: \", task)\n",
    "\n",
    "# data\n",
    "from utils.loader import dataLoader\n",
    "data = dataLoader(config, dataset=task, warp_input=True)\n",
    "train_loader, val_loader = data['train_loader'], data['val_loader']\n",
    "# # data loading\n",
    "# from utils.loader import dataLoader_test as dataLoader\n",
    "# data = dataLoader(config, dataset=task)\n",
    "# test_set, test_loader = data['test_set'], data['test_loader']\n",
    "\n",
    "logging.info('== train split size %d in %d batches, val split size %d in %d batches'%\\\n",
    "        (len(train_loader)*config['model']['batch_size'], len(train_loader),\n",
    "         len(val_loader)*config['model']['batch_size'], len(val_loader)))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "load training samples\n",
      "['image', 'valid_mask', 'labels_2D', 'warped_img', 'warped_labels', 'warped_valid_mask', 'homographies', 'inv_homographies', 'name']\n"
     ]
    }
   ],
   "source": [
    "# # val\n",
    "# for i, sample in enumerate(val_loader):\n",
    "#     if i% 100 == 0:\n",
    "#         print(list(sample))\n",
    "#         break\n",
    "# train\n",
    "print(\"load training samples\")\n",
    "for i, sample in enumerate(train_loader):\n",
    "    if i% 100 == 0:\n",
    "        print(list(sample))\n",
    "        break\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==> Loading pre-trained network.\n",
      "path:  ../deepSfm/logs/superpoint_kitti30_1/checkpoints/superPointNet_170000_checkpoint.pth.tar\n",
      "nms_dist =  4\n",
      "conf_thresh =  0.015\n",
      "nn_thresh =  0.7\n",
      "model structure: relu - bn - conv\n",
      "apply batch norm!\n",
      "==> Successfully loaded pre-trained network.\n",
      "../deepSfm/logs/superpoint_kitti30_1/checkpoints/superPointNet_170000_checkpoint.pth.tar\n"
     ]
    }
   ],
   "source": [
    "device = 'cpu'\n",
    "# get model\n",
    "def loadModel(config, device='cpu'):\n",
    "    from models.model_wrap import SuperPointFrontend_torch\n",
    "\n",
    "    path = config['pretrained']\n",
    "    print('==> Loading pre-trained network.')\n",
    "    print('path: ', path)\n",
    "    # This class runs the SuperPoint network and processes its outputs.\n",
    "\n",
    "    nms_dist = config['model']['nms']\n",
    "    conf_thresh = config['model']['detection_threshold']\n",
    "    nn_thresh = config['model']['nn_thresh']\n",
    "\n",
    "    print('nms_dist = ', nms_dist)\n",
    "    print('conf_thresh = ', conf_thresh)\n",
    "    print('nn_thresh = ', nn_thresh)\n",
    "\n",
    "    fe = SuperPointFrontend_torch(weights_path=path,\n",
    "                            nms_dist=nms_dist,\n",
    "                            conf_thresh=conf_thresh,\n",
    "                            nn_thresh=nn_thresh,\n",
    "                            cuda=False,\n",
    "                            device=device)\n",
    "    print('==> Successfully loaded pre-trained network.')\n",
    "    print(path)\n",
    "    return fe\n",
    "\n",
    "fe = loadModel(config, device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# visualize the matchings\n",
    "import cv2\n",
    "\n",
    "def draw_matches_cv(data):\n",
    "    keypoints1 = [cv2.KeyPoint(p[1], p[0], 1) for p in data['keypoints1']]\n",
    "    keypoints2 = [cv2.KeyPoint(p[1], p[0], 1) for p in data['keypoints2']]\n",
    "    inliers = data['inliers'].astype(bool)\n",
    "    matches = np.array(data['matches'])[inliers].tolist()\n",
    "    def to3dim(img):\n",
    "        if img.ndim == 2:\n",
    "            img = img[:, :, np.newaxis]\n",
    "        return img\n",
    "    img1 = to3dim(data['image1'])\n",
    "    img2 = to3dim(data['image2'])\n",
    "    img1 = np.concatenate([img1, img1, img1], axis=2)\n",
    "    img2 = np.concatenate([img2, img2, img2], axis=2)\n",
    "    return cv2.drawMatches(img1, keypoints1, img2, keypoints2, matches,\n",
    "                           None, matchColor=(0,255,0), singlePointColor=(0, 0, 255))\n",
    "\n",
    "def visualize_matches(image, warped_image, result, filename='test.png'):\n",
    "    from utils.draw import plot_imgs\n",
    "    from utils.utils import pltImshow\n",
    "    # draw matches\n",
    "    result['image1'] = image\n",
    "    result['image2'] = warped_image\n",
    "    img = draw_matches_cv(result)\n",
    "    # filename = \"correspondence_visualization\"\n",
    "    plot_imgs([img], titles=[\"Two images feature correspondences\"], dpi=200)\n",
    "    plt.tight_layout()\n",
    "    plt.savefig(filename, bbox_inches='tight')\n",
    "    plt.close('all')\n",
    "    pltImshow(img)\n",
    "    plt.show()\n",
    "    pass\n",
    "\n",
    "# data = pred\n",
    "# from evaluations.descriptor_evaluation import compute_homography\n",
    "# homography_thresh = [1,3,5]\n",
    "\n",
    "# result = compute_homography(pred, correctness_thresh=homography_thresh)\n",
    "\n",
    "# visualize_matches(squeezeToNumpy(img_0), squeezeToNumpy(img_1), result)\n",
    "\n",
    "# calculate the homography\n",
    "\n",
    "# report the score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['image', 'valid_mask', 'labels_2D', 'warped_img', 'warped_labels', 'warped_valid_mask', 'homographies', 'inv_homographies', 'name']\n",
      "pts_id:  (2, 421)\n",
      "desc:  (256, 421)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[04/25/2019 23:09:53 WARNING] Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "matches:  (62, 4)\n",
      "total points:  (3, 429)\n",
      "pred:  ['image', 'prob', 'desc', 'warped_image', 'matches', 'warped_prob', 'warped_desc', 'homography']\n",
      "shape:  (240, 320)\n",
      "desc:  (421, 256)\n",
      "w desc:  (429, 256)\n",
      "corner:  [[  0   0   1]\n",
      " [  0 239   1]\n",
      " [319   0   1]\n",
      " [319 239   1]]\n",
      "real_warped_corners:  [[-0.09131226 -0.07342697]\n",
      " [-4.71281852 -8.46077979]\n",
      " [-4.62727638  2.76649775]\n",
      " [-4.6080622  -0.57313537]]\n",
      "warped_corners:  [[ -10.4280172     3.49329888]\n",
      " [  14.23346866  748.31747594]\n",
      " [ 233.40775957 -191.25314845]\n",
      " [ 483.09607624  387.60688384]]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[04/25/2019 23:09:54 WARNING] Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## warp image\n",
    "# from utils.utils import pltImshow, saveImg\n",
    "# def tensorto4d(inp):\n",
    "#     if len(inp.shape) == 2:\n",
    "#         inp = inp.view(1, 1, inp.shape[0], inp.shape[1])\n",
    "#     elif len(inp.shape) == 3:\n",
    "#         inp = inp.view(1, inp.shape[0], inp.shape[1], inp.shape[2])\n",
    "#     return inp\n",
    "\n",
    "from imageio import imread\n",
    "def load_as_float(path):\n",
    "    return imread(path).astype(np.float32) / 255\n",
    "\n",
    "def squeezeToNumpy(tensor_arr):\n",
    "    return tensor_arr.detach().cpu().numpy().squeeze()\n",
    "\n",
    "def getTracker(max_length):\n",
    "    from models.model_wrap import SuperPointFrontend, SuperPointFrontend_torch, PointTracker\n",
    "    tracker = PointTracker(max_length, nn_thresh=fe.nn_thresh)\n",
    "    return tracker\n",
    "\n",
    "max_length = 5\n",
    "tracker = getTracker(max_length)\n",
    "\n",
    "outputMatches = True\n",
    "count = 0\n",
    "iter_max = 1\n",
    "\n",
    "# for to get data\n",
    "# export points and descriptors\n",
    "\n",
    "for i, sample in enumerate(train_loader):\n",
    "    if i < iter_max:\n",
    "        print(list(sample))\n",
    "        img_0, img_1 = sample['image'], sample['warped_img']\n",
    "\n",
    "        # first image, no matches\n",
    "        img = img_0\n",
    "        # H, W = img.shape[1], img.shape[2]\n",
    "        # img = img.view(1,1,H,W)\n",
    "\n",
    "        pts, desc, _, heatmap = fe.run(img)\n",
    "        pts = pts[0]\n",
    "        desc = desc[0]\n",
    "        '''\n",
    "        pts: list [numpy (N, 3)]\n",
    "        desc: list [numpy (N, 256)]\n",
    "        '''\n",
    "        if outputMatches == True:\n",
    "            tracker.update(pts, desc)\n",
    "        # save keypoints\n",
    "        pts_id = pts[:2, :]\n",
    "        pred = {'image': squeezeToNumpy(img_0)}\n",
    "        pred.update({'prob': pts.transpose(),\n",
    "                     'desc': desc.transpose()})\n",
    "        \n",
    "        print(\"pts_id: \", pts_id.shape)\n",
    "        print(\"desc: \", desc.shape)\n",
    "\n",
    "        # second image, output matches\n",
    "        img = img_1\n",
    "        pred.update({'warped_image': squeezeToNumpy(img_1)})\n",
    "        pts, desc, _, heatmap = fe.run(img)\n",
    "        pts = pts[0]\n",
    "        desc = desc[0]\n",
    "\n",
    "        if outputMatches == True:\n",
    "            tracker.update(pts, desc)\n",
    "\n",
    "            matches = tracker.get_matches()\n",
    "            print(\"matches: \", matches.transpose().shape)\n",
    "            pred.update({'matches': matches.transpose()})\n",
    "        print(\"total points: \", pts.shape)\n",
    "        pred.update({'warped_prob': pts.transpose(),\n",
    "                     'warped_desc': desc.transpose(),\n",
    "                     'homography': squeezeToNumpy(sample['homographies'])\n",
    "                     })\n",
    "        # clean last descriptor\n",
    "        '''\n",
    "        pred:\n",
    "            'image': np(320,240)\n",
    "            'prob' (keypoints): np (N1, 2)\n",
    "            'desc': np (N2, 256)\n",
    "            'warped_image': np(320,240)\n",
    "            'warped_prob' (keypoints): np (N2, 2)\n",
    "            'warped_desc': np (N2, 256)\n",
    "            'homography': np (3,3)\n",
    "\n",
    "        '''\n",
    "        tracker.clear_desc()\n",
    "        \n",
    "        print(\"pred: \", list(pred))\n",
    "        \n",
    "        # viualize matches\n",
    "        data = pred\n",
    "        from evaluations.descriptor_evaluation import compute_homography\n",
    "        homography_thresh = [1,3,5]\n",
    "\n",
    "        result = compute_homography(pred, correctness_thresh=homography_thresh)\n",
    "\n",
    "        visualize_matches(squeezeToNumpy(img_0), squeezeToNumpy(img_1), result)\n",
    "        \n",
    "    else: break\n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "not take care of batch! only take first element!\n",
      "heatmap:  (244, 324)\n",
      "patches:  torch.Size([1, 429, 5, 5])\n",
      "pts:  (429, 3)\n",
      "dxdy:  torch.Size([1, 429, 2])\n",
      "[array([[2.81998908e+02, 1.85000578e+02, 1.32998591e+02, ...,\n",
      "        2.91000622e+02, 2.59000417e+02, 5.29998940e+01],\n",
      "       [8.50017831e+01, 1.69000720e+02, 1.09996933e+02, ...,\n",
      "        4.99996590e+01, 6.19995799e+01, 2.02001682e+02],\n",
      "       [3.72512370e-01, 2.51099437e-01, 2.28458136e-01, ...,\n",
      "        1.51691502e-02, 1.51569685e-02, 1.51355835e-02]])]\n"
     ]
    }
   ],
   "source": [
    "points = fe.soft_argmax_points()\n",
    "# print(\"points: \", points.shape)\n",
    "print(points)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "get pts\n",
      "[[2.82000000e+02 1.85000000e+02 1.33000000e+02 ... 2.91000000e+02\n",
      "  2.59000000e+02 5.30000000e+01]\n",
      " [8.50000000e+01 1.69000000e+02 1.10000000e+02 ... 5.00000000e+01\n",
      "  6.20000000e+01 2.02000000e+02]\n",
      " [3.72512370e-01 2.51099437e-01 2.28458136e-01 ... 1.51691502e-02\n",
      "  1.51569685e-02 1.51355835e-02]]\n"
     ]
    }
   ],
   "source": [
    "points = fe.points\n",
    "print(points[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "pts = points[0]\n",
    "# pts = pts[[1, 0], :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[04/25/2019 23:16:45 WARNING] Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "img_1:  torch.Size([1, 1, 240, 320])\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "heatmap:  0.0035829938\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# print image with points\n",
    "from utils.draw import draw_keypoints\n",
    "from utils.utils import toNumpy\n",
    "\n",
    "print(\"img_1: \", img_1.shape)\n",
    "\n",
    "img = draw_keypoints(toNumpy(img_1.squeeze()), pts)\n",
    "# print(\"img: \", img_0)\n",
    "plt.imshow(img)\n",
    "plt.show()\n",
    "\n",
    "\n",
    "print(\"heatmap: \", toNumpy(heatmap).mean())\n",
    "plt.imshow(toNumpy(heatmap.squeeze()))\n",
    "plt.show()\n",
    "\n",
    "\n",
    "# extract patches\n",
    "\n",
    "# do soft argmax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "points:  (3, 443)\n",
      "point:  [263.         188.           0.39999139]\n"
     ]
    }
   ],
   "source": [
    "print(\"points: \", pts.shape)\n",
    "point = pts[:,0]\n",
    "print(\"point: \", point)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "heatmap:  (244, 324)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n",
      "patch:  (5, 5)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "patches:  torch.Size([1, 12, 5, 5])\n"
     ]
    }
   ],
   "source": [
    "def extract_patch(heatmap, points, patch_size=5):\n",
    "    # numpy\n",
    "    heatmap = toNumpy(heatmap).squeeze()  # [H, W]\n",
    "    # padding\n",
    "    pad_size = int(patch_size/2)\n",
    "    heatmap = np.pad(heatmap, pad_size, 'constant')\n",
    "    # crop it\n",
    "    patches = []\n",
    "    ext = lambda img, pnt, wid: img[pnt[1]:pnt[1]+wid, pnt[0]:pnt[0]+wid]\n",
    "    print(\"heatmap: \", heatmap.shape)\n",
    "    for i in range(points.shape[0]):\n",
    "#         print(\"point: \", points[i,:])\n",
    "        patch = ext(heatmap, points[i,:].astype(int), patch_size)\n",
    "        print(\"patch: \", patch.shape)\n",
    "        patches.append(patch)\n",
    "        \n",
    "        if i > 10: break\n",
    "    # extract points\n",
    "    return patches\n",
    "    \n",
    "patches = extract_patch(heatmap, pts.transpose(), patch_size=5)\n",
    "# print(\"patches\", patches)\n",
    "for i in patches:\n",
    "    plt.imshow(i)\n",
    "    plt.show()\n",
    "\n",
    "import torch\n",
    "patches = np.stack(patches)\n",
    "patches_torch = torch.tensor(patches, dtype=torch.float32).unsqueeze(0)\n",
    "print(\"patches: \", patches_torch.shape)\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(x_coord, x_coord) tensor([[[ 0.0038],\n",
      "         [-0.0067],\n",
      "         [-0.0016],\n",
      "         [ 0.0002],\n",
      "         [-0.0010],\n",
      "         [ 0.0022],\n",
      "         [-0.0053],\n",
      "         [-0.0035],\n",
      "         [-0.0030],\n",
      "         [-0.0046],\n",
      "         [ 0.0037],\n",
      "         [-0.0038]]]) tensor([[[-5.9551e-04],\n",
      "         [ 2.9786e-04],\n",
      "         [-1.3602e-03],\n",
      "         [ 1.5780e-04],\n",
      "         [ 4.5662e-03],\n",
      "         [ 2.4125e-04],\n",
      "         [ 4.0180e-03],\n",
      "         [ 1.6454e-03],\n",
      "         [-1.8921e-03],\n",
      "         [-2.3226e-03],\n",
      "         [-5.0900e-03],\n",
      "         [-7.4659e-05]]])\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import torchgeometry as tgm\n",
    "\n",
    "# input = torch.rand(1, 4, 2, 3)\n",
    "input = patches_torch\n",
    "m = tgm.contrib.SpatialSoftArgmax2d()\n",
    "coords = m(input)  # 1x4x2\n",
    "x_coord, y_coord = torch.chunk(coords, dim=-1, chunks=2)\n",
    "\n",
    "print(\"(x_coord, x_coord)\", x_coord, y_coord)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "squeezeToNumpy(img_1).shape\n",
    "# matches(squeezeToNumpy(img_0), squeezeToNumpy(img_1), result)\n",
    "list(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(list(result))\n",
    "print(\"correctness: \", result['correctness'])\n",
    "print(\"gt homography: \", data['homographies'])\n",
    "print(\"est homography: \", result['homography'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from utils.draw import plot_imgs\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## visualize data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# print shape\n",
    "entries = list(sample)\n",
    "for i in entries:\n",
    "    element = sample[i]\n",
    "#     print(type(element))\n",
    "    if type(element) is torch.Tensor:\n",
    "        print(\"shape of \", i, \" \", element.shape)\n",
    "img, labels_2D, mask_2D = sample['image'], sample['labels_2D'], sample['valid_mask']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def img_overlap(img_r, img_g, img_gray):  # img_b repeat\n",
    "    img = np.concatenate((img_gray, img_gray, img_gray), axis=0)\n",
    "    img[0, :, :] += img_r[0, :, :]\n",
    "    img[1, :, :] += img_g[0, :, :]\n",
    "    img[img > 1] = 1\n",
    "    img[img < 0] = 0\n",
    "    img = img.transpose([1,2,0])\n",
    "    return img\n",
    "def toNumpy(tensor):\n",
    "    return tensor.detach().cpu().numpy()\n",
    "\n",
    "result_overlap = img_overlap(toNumpy(1 - mask_2D[0,:,:,:]), toNumpy(labels_2D[0, :, :, :]), toNumpy(img[0, :, :, :]))\n",
    "print(result_overlap.shape)\n",
    "\n",
    "plt.imshow(result_overlap)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize warped images (for joint training)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# entries = ['image', 'labels_2D', 'valid_mask', 'overlay']\n",
    "entries = ['warped_img', 'warped_labels', 'warped_valid_mask', 'overlay']\n",
    "cols = len(entries)\n",
    "scale = 10\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# show images\n",
    "count = 1\n",
    "images_num = 2\n",
    "col_row_ratio = 3\n",
    "rows = images_num\n",
    "plt.figure(figsize=(cols*col_row_ratio*scale, rows*scale))\n",
    "\n",
    "task_folder = ['matching']\n",
    "for i in range(images_num):\n",
    "    for j in range(cols):\n",
    "#         exp_path = Path(base_path, folder[j], prediction, task_folder[0])\n",
    "#         path = exp_path / (str(i) + 'm.png')\n",
    "#         image = load_as_float(path)\n",
    "        print(entries[j])\n",
    "\n",
    "        if entries[j] == 'overlay':\n",
    "            img, labels_2D, mask_2D = sample[entries[0]], sample[entries[1]], sample[entries[2]]\n",
    "            image = img_overlap(toNumpy(1 - mask_2D[i,:,:,:]), \n",
    "                toNumpy(labels_2D[i, :, :, :]), toNumpy(img[i, :, :, :]))\n",
    "        else:\n",
    "            image = sample[entries[j]][i,0,:,:]\n",
    "            image = image.numpy()\n",
    "        plt.subplot(rows, cols, count)\n",
    "        count += 1\n",
    "        plt.axis('off')\n",
    "        plt.title(entries[j] + '/' + str(i))\n",
    "        plt.imshow(image, cmap='gray')\n",
    "        plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize images w/o homography augmentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "entries = ['image', 'labels_2D', 'valid_mask', 'overlay']\n",
    "# entries = ['warped_img', 'warped_labels', 'warped_valid_mask', 'overlay']\n",
    "cols = len(entries)\n",
    "scale = 10\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# show images\n",
    "count = 1\n",
    "images_num = 2\n",
    "col_row_ratio = 3\n",
    "rows = images_num\n",
    "plt.figure(figsize=(cols*col_row_ratio*scale, rows*scale))\n",
    "\n",
    "task_folder = ['matching']\n",
    "for i in range(images_num):\n",
    "    for j in range(cols):\n",
    "#         exp_path = Path(base_path, folder[j], prediction, task_folder[0])\n",
    "#         path = exp_path / (str(i) + 'm.png')\n",
    "#         image = load_as_float(path)\n",
    "        print(entries[j])\n",
    "\n",
    "        if entries[j] == 'overlay':\n",
    "            img, labels_2D, mask_2D = sample[entries[0]], sample[entries[1]], sample[entries[2]]\n",
    "            image = img_overlap(toNumpy(1 - mask_2D[i,:,:,:]), \n",
    "                toNumpy(labels_2D[i, :, :, :]), toNumpy(img[i, :, :, :]))\n",
    "        else:\n",
    "            image = sample[entries[j]][i,0,:,:]\n",
    "            image = image.numpy()\n",
    "        plt.subplot(rows, cols, count)\n",
    "        count += 1\n",
    "        plt.axis('off')\n",
    "        plt.title(entries[j] + '/' + str(i))\n",
    "        plt.imshow(image, cmap='gray')\n",
    "        plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mask_2D.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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